SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING, cilt.33, sa.4, ss.94-108, 2022 (SCI-Expanded)
Steadily increasing demand requires
neonatal units and networks to improve their overall capacities. Given the
operational complexities involved, simulation is a popular choice for modelling
patient flow and analysing its impact on resource capacities. Clinical pathways,
designed to reduce variation of care and improve the quality of care for a
specific group of patients, broadly define patient flow patterns. The
literature points to many simulation studies where the interactions between
clinical pathways and resource planning have been addressed. For efficient
model building, these simulation studies have, however. assumed a unidirectional
flow of patients, i.e., progressively moving to lower levels of care. Patient
flows are, however, much more complex. In some instances, patients may require
a higher level of care than the current level of care. In such cases,
bi-directional flows are created. This paper explores the impact of
bidirectional flows on capacity planning. Using a real-world neonatal unit as
an example, two scenarios of patient flow, i.e., unidirectional and
bidirectional, are modelled and extensively analysed. This study revealed that
the bidirectional flow model, which is the more realistic model, produces
significantly different capacity planning estimates. For example, the number of
admission requests rejected by the unit increased by 5-7 times, i.e., the
uni-directional model significantly underestimates the overall capacity. The
bidirectional model also revealed that there is a need to double the number of
beds required for high-level care, and bed utilisation, in general, is higher
than the estimates produced by the unidirectional model. Given that there is a
need to generate accurate capacity estimates to ensure better services for
patients and minimise regular changes due to poor capacity estimates, this
paper argues that bidirectional modelling should be used to produce more
accurate capacity estimates.